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The Award database is continually updated throughout the year. As a result, data for FY21 is not expected to be complete until September, 2022.

Download all SBIR.gov award data either with award abstracts (290MB) or without award abstracts (65MB). A data dictionary and additional information is located on the Data Resource Page. Files are refreshed monthly.

  1. Bounding generalization risk for Deep Neural Networks

    SBC: Euler Scientific            Topic: NGA20A001

    Deep Neural Networks have become ubiquitous in the modern analysis of voluminous datasets with geometric symmetries. In the field of Particle Physics, experiments such as DUNE require the detection of particle signatures interacting within the detector, with analyses of over a billion 3D event images per channel each year; with typical setups containing over 150,000 different channels.  In an ...

    STTR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency
  2. IA 2: Intent-Capturing Annotations for Isolation and Assurance

    SBC: Immunant, Inc.            Topic: HR001120S0019001

    Software and hardware flaws can be exploited to make programs perform unintended computations or leak sensitive data. We propose to counter these threats by isolating libraries and other program units inside a single process. The developer will insert source-level annotations that i) map code and data units to compartments and ii) capture how each compartment is intended to interact with others, i ...

    STTR Phase I 2020 Department of DefenseDefense Advanced Research Projects Agency
  3. MORTIMER: Language Mechanisms and Tools for Run-TIme Memory Access Policy Enforcement

    SBC: INTELLIGENT AUTOMATION, INC.            Topic: HR001120S0019001

    DoD has a critical need for protecting sensitive data to make sure that only the intended, trusted programs or parts of programs can access the data. This protection must be also effective when data is loaded into memory while being processed by software. Lately, the side-channel attacks which are based on information gained from the implementation of a computer system rather than exploiting algor ...

    STTR Phase I 2020 Department of DefenseDefense Advanced Research Projects Agency
  4. Patterned, Responsive Cellular Therapies Using Novel Mammalian Cellular Regulator Systems

    SBC: General Biologics, Inc.            Topic: HR001119S003516

    We propose to design, build and test genetic circuits and DNA constructs that will be expressed in human cells and that will ultimately have applications for the health of warfighters. The circuits will have physiological inputs representing, for example, (1) infection/sepsis, (2) altitude sickness or blood loss, and (3) radiation exposure; which will be mediated through signal transduction pathwa ...

    STTR Phase I 2020 Department of DefenseDefense Advanced Research Projects Agency
  5. Sparse Information Orbit Estimation for Proliferated LEO

    SBC: Braxton Technologies, LLC            Topic: HR001119S003522

    Rapidly expanding Low Earth Orbit (LEO) satellite constellations force traditional ground-based tracking methods to adapt as the current ground sensor networks can no longer provide a data rich tracking environment. Accurate tracking information is continually consumed by the Government and private sector to varying degrees of accuracy throughout satellites’ mission lifecycles to provide and uti ...

    STTR Phase I 2020 Department of DefenseDefense Advanced Research Projects Agency
  6. Continuum Actuated Redundant Tendon Robots

    SBC: Opterus Research and Development, Inc.            Topic: HR001119S003523

    Opterus Research and Development, Inc. (Opterus) and Colorado State University (CSU) have combined the best features of high strain composites (HSC), continuum robots, and tendon actuated robots to develop a new concept called Continuum Actuated Redundant Tendon (CART) Robot to enable self-reconfigurable modular robots that can perform various tasks (e.g., walking, crawling, wheeling, and grasping ...

    STTR Phase I 2020 Department of DefenseDefense Advanced Research Projects Agency
  7. Variable Leg Length Ground Robot with Novel Prismatic Actuators

    SBC: Triton Systems, Inc.            Topic: HR001119S003523

    Triton Systems, Inc. will work in collaboration with Professor Mark Yim of the University of Pennsylvania (UPenn) to design a viable, robust ground robot with novel, reconfigurable actuators. This robot can reconfigure from a wheeled state to a legged state, enabling it to overcome tall obstacles and rough terrain. This ground robot will also be of a modular nature, able to be combined with others ...

    STTR Phase I 2020 Department of DefenseDefense Advanced Research Projects Agency
  8. Self-driving Modular AI-based Robot for Rough Terrain (SMARRT)

    SBC: INTELLIGENT AUTOMATION, INC.            Topic: HR001119S003523

    The Defense Advanced Research Projects Agency (DARPA) is seeking to utilize small reconfigurable robotic system to operate independently in unknown highly complex environments. We propose a modular reconfigurable robot, which presents several locomotion modality to handle different type of off-road environments. We proposed several configurations for the robot, which are well-suited to the type of ...

    STTR Phase I 2020 Department of DefenseDefense Advanced Research Projects Agency
  9. Aberration-correcting Topologically Optimized Metasurface (ATOM)

    SBC: Physical Sciences Inc.            Topic: HR001119S003524

    Metalenses, with their ability to arbitrarily control the amplitude and phase of light across a band of wavelengths, have the potential to disrupt imaging and communication systems which rely on traditional lenses to focus, collimate, and otherwise manipulate optical signals, and are under increasing pressure to operate with reduced size and weight. We propose to design, develop, and demonstrate a ...

    STTR Phase I 2020 Department of DefenseDefense Advanced Research Projects Agency
  10. Machine Learning and Data Fusion platform for Phenotype-based Pathogen Identification

    SBC: Triton Systems, Inc.            Topic: ST18C002

    Conventional methods for detecting pathogens, which are based on culturing the microorganism, are time-consuming and laborious. Machine learning provides an alternative path to identify pathogens using supervised learning algorithms. Most current computational tools utilize genomic or protein data to identify bacteria. These methods look for features in the whole genome that correlate to pathogeni ...

    STTR Phase I 2019 Department of DefenseDefense Advanced Research Projects Agency
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